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PhoenixAI

Real-time analytical database for AI agents

Presales Solutions Architect

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USARemote

About the Job

Requirements

  • At least 3 years of experience in a presales, solutions engineering, or technical consulting role; experience in data analytics, databases, or cloud infrastructure is ideal.
  • Hands-on experience with OLAP workloads, query optimization, and data modeling, including star and snowflake schemas.
  • Proficiency in SQL.
  • Deep understanding of distributed data processing system theory.
  • Familiarity with at least one public cloud platform: AWS, GCP, or Azure.
  • Ability to explain complex technical concepts clearly to diverse stakeholders, including engineers and C-level executives.
  • Ability to troubleshoot technical challenges during proofs of concept and adapt solutions to customer needs.
  • Experience supporting sales teams in technical evaluations, with a track record of securing technical wins and driving revenue growth.

Responsibilities

  • Partner with the sales team to guide prospects through technical evaluations of PhoenixAI’s Agentic Database and secure technical wins.
  • Demonstrate the platform’s capabilities, including its vectorized query engine, lakehouse analytics, and multi-table joins for agentic AI workloads, through presentations, customized demos, and proofs of concept.
  • Understand prospects’ needs, such as data scale, latency, and integrations, and architect tailored PhoenixAI-based solutions.
  • Lead the design, implementation, and optimization of proofs of concept to demonstrate the platform’s performance and usability.
  • Document evaluations, including use cases, challenges, proof-of-concept plans, and outcomes, to improve the process and inform product enhancements.
  • Coordinate technical discussions with business goals, address objections, help close deals, and gather customer insights to shape the product roadmap with product and engineering teams.
  • Deliver webinars, staff conference booths, speak at user groups, and write blogs about agentic AI use cases and best practices.

Desired Qualifications

  • Knowledge of business intelligence tools such as Tableau or Looker.
  • Experience with streaming processing systems such as Kafka or Redpanda.

About the Company

PhoenixAI

Real-time analytical database for AI agents

PhoenixAI builds real-time analytic databases for AI agents and applications. Its engine ingests streaming data (Kafka, Flink CDC) and reads lakehouse tables (Iceberg, Delta Lake, Hudi) in place, then joins fresh data with historical data in a single query to deliver sub-second SQL without precomputation. It offers isolated multi-warehouse compute so agent workloads, BI, and data ingestion run side-by-side without competition for resources, with monitoring, security, and access controls. Customers can use a cloud-hosted managed version (PhoenixAI Cloud) deployed in their cloud account, or a self-managed Kubernetes version (PhoenixAI Anywhere) in their environment. The company centers its product on an open-source core (StarRocks) and adds extra security, governance, and support under commercial contracts. The goal is to provide fast, reliable, and secure real-time analytics for AI workloads and data teams, enabling seamless querying across streaming and historical data.

Company size
51-200
Company stage
Series B
Total funding
$80M
Headquarters
Menlo Park, CA
Founded
2022

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